Mingxu Zhu, Yu Wang, Junyao Li, Weice Wang, Guobin Gao, Zhenyu Ji, Benyuan Liu, Lei Wang, Weichen Li, Xuetao Shi
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EIT perfusion images were obtained by calculating the impedance difference between at the beginning and end of cerebral vasodilation. Subsequently, GI and AI were calculated based on the pixel values of intracranial regions.</p><p><strong>Results: </strong>The GI and AI values in the non-carotid artery compression (NCAC) group were significantly lower than those in the unilateral carotid artery compression (UCAC) group (P < 0.001), whereas there was no significant difference between the left carotid artery compression (LCAC) and right carotid artery compression (RCAC) groups. ROC analysis showed that the area under the curve (AUC), specificity and sensitivity of GI in distinguishing between NCAC and UCAC were 0.94, 0.90 and 0.87, respectively. The AUC, specificity and sensitivity of AI in distinguishing between NCAC and UCAC were 0.86, 0.87 and 0.73, respectively.</p><p><strong>Conclusion: </strong>The results demonstrated that the GI and AI effectively quantify the distribution of intracranial perfusion, demonstrating excellent validity and interindividual comparability, and the ability to detect abnormal cerebral perfusion heterogeneity.</p>","PeriodicalId":12477,"journal":{"name":"Frontiers in Physiology","volume":"15 ","pages":"1476040"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11599225/pdf/","citationCount":"0","resultStr":"{\"title\":\"Evaluation of cerebral perfusion heterogeneity by the electrical impedance tomography.\",\"authors\":\"Mingxu Zhu, Yu Wang, Junyao Li, Weice Wang, Guobin Gao, Zhenyu Ji, Benyuan Liu, Lei Wang, Weichen Li, Xuetao Shi\",\"doi\":\"10.3389/fphys.2024.1476040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The purpose of this study was to evaluate the ability of global inhomogeneity index (GI) and left-right asymmetry index (AI) based on electrical impedance tomography (EIT) to be used in assessing cerebral perfusion heterogeneity. 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引用次数: 0
摘要
目的:本研究旨在评估基于电阻抗断层扫描(EIT)的总体不均匀指数(GI)和左右不对称指数(AI)用于评估脑灌注异质性的能力。研究还探讨了这两个指数在识别脑灌注异质性程度异常方面的诊断价值:在这项研究中,经颅多普勒(TCD)被用作对照,单侧颈动脉被压缩,以改变 15 名健康志愿者的脑灌注异质性程度。对照组由另外 15 名未进行任何干预的志愿者组成。通过计算脑血管扩张开始和结束时的阻抗差,获得 EIT 灌注图像。随后,根据颅内区域的像素值计算 GI 和 AI:结果:非颈动脉压迫(NCAC)组的 GI 值和 AI 值明显低于单侧颈动脉压迫(UCAC)组(P < 0.001),而左侧颈动脉压迫(LCAC)组和右侧颈动脉压迫(RCAC)组之间无明显差异。ROC 分析显示,GI 在区分 NCAC 和 UCAC 方面的曲线下面积(AUC)、特异性和灵敏度分别为 0.94、0.90 和 0.87。AI区分NCAC和UCAC的AUC、特异性和灵敏度分别为0.86、0.87和0.73:结果表明,GI 和 AI 能有效量化颅内灌注的分布,具有良好的有效性和个体间可比性,并能检测异常脑灌注异质性。
Evaluation of cerebral perfusion heterogeneity by the electrical impedance tomography.
Purpose: The purpose of this study was to evaluate the ability of global inhomogeneity index (GI) and left-right asymmetry index (AI) based on electrical impedance tomography (EIT) to be used in assessing cerebral perfusion heterogeneity. The diagnostic value of these two indices in identifying abnormalities in the degree of cerebral perfusion heterogeneity was also explored.
Methods: In this study, Transcranial Doppler (TCD) was used as a control, and unilateral carotid artery was compressed to change the degree of heterogeneity of cerebral perfusion in 15 healthy volunteers. The control group consisted of an additional 15 volunteers without any intervention. EIT perfusion images were obtained by calculating the impedance difference between at the beginning and end of cerebral vasodilation. Subsequently, GI and AI were calculated based on the pixel values of intracranial regions.
Results: The GI and AI values in the non-carotid artery compression (NCAC) group were significantly lower than those in the unilateral carotid artery compression (UCAC) group (P < 0.001), whereas there was no significant difference between the left carotid artery compression (LCAC) and right carotid artery compression (RCAC) groups. ROC analysis showed that the area under the curve (AUC), specificity and sensitivity of GI in distinguishing between NCAC and UCAC were 0.94, 0.90 and 0.87, respectively. The AUC, specificity and sensitivity of AI in distinguishing between NCAC and UCAC were 0.86, 0.87 and 0.73, respectively.
Conclusion: The results demonstrated that the GI and AI effectively quantify the distribution of intracranial perfusion, demonstrating excellent validity and interindividual comparability, and the ability to detect abnormal cerebral perfusion heterogeneity.
期刊介绍:
Frontiers in Physiology is a leading journal in its field, publishing rigorously peer-reviewed research on the physiology of living systems, from the subcellular and molecular domains to the intact organism, and its interaction with the environment. Field Chief Editor George E. Billman at the Ohio State University Columbus is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.